Modeling of Water Main Failure Rates Using the Log-linear ROCOF and the Power Law Process

Park, S.; Jun, Hwandon; Kim, B. J.; Im, G. C.

doi:10.1007/s11269-007-9227-3

Cited by 28 publications

(21 citation statements)

References 15 publications

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“…To achieve this, Christodoulou and Deligianni (2010) used neurofuzzy decision framework. Other technique found in literature is in the work by Park et al (2008), who use log-linear ROCOF and the power law process to model the failure rate and estimate the economically optimal replacement time of the individual pipes.…”

mentioning

confidence: 99%

Evaluation of the Reliability of a Water Supply Network from Right-Censored and Left-Truncated Break Data

Carrión

Solano

Gámiz

et al. 2010

Water Resour Manage

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In this paper, we analyze failure data registered in a water supply network in order to evaluate the pipes failure probability. Only failures in normal operation conditions have been considered, excluding those caused by abnormal events. We consider an observation window from year 2000 until 2005, although the life of some of the water pipes started far in the past. This sampling scheme induces left-truncation into the data set (since failures before 2000 are not considered into the sample information) and right-censoring (for pipes that fail after 2005). We used an extended version of the Nelson–Aalen estimator, modified in order to accommodate left-truncation besides right-censoring (LTRC). Influencing factors on water pipes survival are identified. By the use of a semiparametric model based on the Cox proportional hazards model, also adapted to manage left-truncated and right-censored data, the effect of each factor over the failure risk of a pipe section has been estimated

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mentioning

confidence: 99%

Evaluation of the Reliability of a Water Supply Network from Right-Censored and Left-Truncated Break Data

Carrión

Solano

Gámiz

et al. 2010

Water Resour Manage

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“…The pipe based models work with homogenous pipes (same environmental and network features) and applies ROCOF function to each of them. However, at least five historical failures per pipes are necessary to estimate the ROCOF functions [17]. So many known failures rarely happen in practice.…”

Section: • Mechanistic Modelsmentioning

confidence: 99%

A Spatial probabilistic model of pipeline failures

Bogárdi¹,

Fülöp

2011

Per. Pol. Civil Eng.

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A spatial probabilistic model is developed and applied to predict failure patterns over a water supply pipe network. The Zalaegerszeg waterworks is used to illustrate the methodology. The ageing of water supply pipes is a worldwide concern; therefore it is of high interest to identify the best interventions in time and space. Two-part models can be used; one is an economic by formulating time horizon total costs. The other part forecasts the break patterns in time and space. Spatial modeling is necessary since elements of the cost function depend on the location of failures. A network based model is developed for the internal part of the Zalaegerszeg waterworks since the system is homogeneous in a sense that the environmental and network features do not exhibit significant correlation with the occurrence of failures. Network based failure probabilities are described by a spacetime Poisson process where non-homogeneous Poisson process (NHPP) refers to time and a stochastic point process refers to space. To estimate the intensity the whole area is covered by a grid system of 250 × 250 meters with an average pipe length of 703 meter in a cell. Both the number of and the distance between failures prove the applicability of the Poisson process. It is shown how a simulation procedure can be applied to generate possible pipe failure patterns which -by combining with the spatial cost functions -leads to estimate total costs per selected time periods.

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“…Other techniques found in literature include the work by Park et al (2008), and Ekinci and Konak (2009). Park et al (2008) presented and compared applications of a the log-linear ROCOF method and the power law process to model pipe failure rates and to estimate economically optimal replacement times, concluding that the log-linear ROCOF method performed better.…”

Section: State Of Knowledgementioning

confidence: 99%

“…Park et al (2008) presented and compared applications of a the log-linear ROCOF method and the power law process to model pipe failure rates and to estimate economically optimal replacement times, concluding that the log-linear ROCOF method performed better. Furthermore, they concluded that recording each failure time results in better modelling of the failure rate than observing failure numbers in some time intervals.…”

Section: State Of Knowledgementioning

confidence: 99%

A Neurofuzzy Decision Framework for the Management of Water Distribution Networks

Christodoulou

Deligianni

2009

Water Resour Manage

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Among the most important components of sustainable management strategies for water distribution networks is the ability to integrate risk analysis and asset management decision-support systems (DSS), as well as the ability to incorporate in the analysis financial and socio-political parameters that are associated with the networks in study. Presented herein is a neurofuzzy decision-support system for the performance of multi-factored risk-of-failure analysis and pipe asset management, as applied to urban water distribution networks. The study is based on two datasets (one from New York City and the other from the city of Limassol, Cyprus), analytical and numerical methods, and artificial intelligence techniques (artificial neural networks and fuzzy logic) that capture the underlying knowledge and transform the patterns of the network's behaviour into a knowledge-repository and a DSS.

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Modeling of Water Main Failure Rates Using the Log-linear ROCOF and the Power Law Process

Cited by 28 publications

References 15 publications

Evaluation of the Reliability of a Water Supply Network from Right-Censored and Left-Truncated Break Data

Evaluation of the Reliability of a Water Supply Network from Right-Censored and Left-Truncated Break Data

A Spatial probabilistic model of pipeline failures

A Neurofuzzy Decision Framework for the Management of Water Distribution Networks

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